README
"How to assess power law behavior using stochastic process methods: A note of caution"
matthias.fatke@uni-konstanz.de
06.05.2019


DESCRIPTION
The material replicates the analysis in "How to assess power law behavior using stochastic process methods: A note of caution".
It includes R code as well as data on real annual outlays for the U.S. government 1800-2004. The data includes defense, domestic, and total outlays.
Please note: The data was collected by Christian Breunig and Bryan D. Jones and published previously (doi:10.1093/pan/mpq038). Please cite their work when referring to the data.
The code is adapted from vignettes of the poweRlaw package by Gillespie (2015) available at https://rdrr.io/cran/poweRlaw/ as well as from the replication material by Breunig and Jones (2011) available at https://www.polver.uni-konstanz.de/breunig/team/breunig/
Credit belongs to them.


RUNNING TIME
The following running times (in minutes) were clocked on a personal computer equipped with four Intel Core i7-8550U CPUs @ 1.80GHz, 16GB of RAM, and a Windows 10 operating system:
Main part: 4.278665
Appendix: 10.16878
Total: 14.44744


MINIMUM REQUIREMENTS
The R script can be run on most modern computers. I recommend using a 64-bit operating system, a 2 core computer with a minimum of 2 GB of RAM. The entire environment will take up less than 1 MB of disk space.


PACKAGE REQUIREMENTS
The results were computed using R 3.5.1. The R script for the main part requires installing the packages 'poweRlaw' and 'tidyverse'. The R script for the Appendix additionally requires installing the package 'MASS'.


OUTPUT
The R script of the main part saves the ouputs of the following figures and tables:
table1.csv
table2.csv
figure1.pdf

The R script of the Appendix saves the ouputs of the following figures and tables:
tableA1.csv
tableA2.csv
tableA3.csv
figureA1.pdf
figureA2.pdf
figureA3.pdf